## Overview

### Current Efforts

The survey sub-team is focused on monitoring diversity and exploring obstacles, motivations, and involvement of useRs in the community. Diversity will be monitored via basic demographic summaries from specifically designed surveys or other community surveys (e.g. useR! feedback survey).

### Former Efforts

The taskforce collates data on the gender breakdown and other demographics of contributors to the R project, particularly R Foundation supported activities. For many of the gender summaries the gender is predicted based on first name, giving a rough approximation that assumes binary gender categories.

## Packages

### Maintainer Gender 2016

CRAN maintainers as of March 2016 were processed with the **genderizer**
package, which utilizes the https://genderize.io/ API to predict gender from
first names, with an associated probability that the prediction is correct. In
some cases genderize.io fails to make a prediction, particularly
for Asian names, so the results were supplemented by manual predictions based on
personal knowledge (with help from Chinese colleagues).

Using assignments as given, i.e. treating predictions with probability > 0.5 as correct, 14.8% of the 7854 maintainers were predicted as female. Clearly this is a rough estimate as not all maintainers with the same name will share the same gender. The frequencies could be adjusted by the probabilities, but this would over-estimate the proportion of female maintainers as the probabilities are based on a general population rather than the population of programmers, which is known to be male-dominated. For example genderize.io assigns the name “Robin” as female with probability 0.59, however the proportion of females among CRAN maintainers with the name Robin is around 10%. So a better estimate is obtained by focusing on names that are strongly predictive of gender, i.e. with probability at least 0.8, giving an estimate of 11.4%.

### Author Demographics 2010

Mair, P., Hofmann, E., Gruber, K., Hatzinger, R., Zeleis, A. and Hornik, K. (2015) Motivation, values, and work design as drivers of participation in the R open source project for statistical computing, *PNAS* describes the feedback from 1087 R package authors. The survey was conducted in 2010. Package authors were contacted by email and asked to complete a web form, with a response rate of 27%.

- The 95% confidence interval for the proportion of women package authors in 2010 is 7.1-11.0%.
- 32.5% of authors are from the USA, but they are distributed across the globe, including Indonesia, Kenya, Slovenia and Singapore.
- The average package author was almost 39 years old, 50% of authors are between 30 and 45, and the youngest was 20.

## Conferences

Data is being collated on past useR! conferences, the plots below show the data gathered so far.

The proportion of contributed presentations is similar to the proportion of female attendees, showing that women are as likely to contribute and have their contributions accepted as their male counterparts. There was a greater increase in poster contributions from women than lightning or regular talks in 2016, which perhaps reflects a lower level of experience among the newcomers.

Plot **c** shows groups that are more heavily selected. The numbers of female
invited speakers has increased from zero in the early years (2004-2008) through
one in later years (2009-2013) to two in recent years - this is the level that
useR! is seeking to maintain for now. The number of tutorials with a female tutor was
decreasing since 2007, but went up again to ^{1}⁄_{3} in 2016. This is the target for
2017. useR! does not always have panel sessions, but apart from a panel in 2014
on women in the R community, women have been poorly represented. This is
something useR! plans to address in any future panels.

The last plot shows invited organisational roles. Data on session chairs is only available for a few years, but recently the proportion of women has been similar that of attendees. The proportion of female committee members has been slowly rising to parity over the history of useR! (with an unusual high in 2007 when Di Cook, a taskforce member was a key organiser). The make-up of the local organising committee is much more variable, partly because the size of the committee changes a lot according to local needs. In recent years the proportion of women on the committee has been similar to or greater than that of attendees.